WOFOST伴随率定三温模型的玉米农田遥感蒸散发估算方法

doi:10.13866/j.azr.2025.01.15

Abstract

Abstract:

The method for estimating evapotranspiration using remote sensing evapotranspiration models has been widely applied, but there is need for research into improving its accuracy. Crop growth models exhibit strong mechanistic foundations and accuracy in simulating crop transpiration. This study integrated the WOFOST crop growth model with the three-temperature remote sensing evapotranspiration model to design a novel method for estimating remote sensing-based evapotranspiration in maize fields. The core approach involved localizing the WOFOST model, validating its simulation accuracy, and using its simulated crop transpiration data to construct an auxiliary calibration function. This function calibrated the transpiration component of the three-temperature model and combined it with the calibrated soil evaporation component to derive the evapotranspiration for the maize fields. Using actual evapotranspiration observed by an eddy covariance system as a reference, the estimation accuracy and applicability of the novel method were evaluated. The results showed that the correlation coefficients of evapotranspiration, crop transpiration, and soil evaporation in the uncalibrated three-temperature model were 0.61, 0.71, and 0.12, respectively, with root mean square errors (RMSE) of 1.76 mm·d^-1, 1.91 mm·d^-1, and 3.02 mm·d^-1, respectively, and negative Nash-Sutcliffe efficiency coefficients. After calibrating only the soil evaporation component, the correlation coefficients improved to 0.77, but the error remained large (1.91 mm·d^-1) with a Nash-Sutcliffe efficiency coefficient of -0.74. However, when the three-temperature model was calibrated using the WOFOST-simulated crop transpiration data, the correlation coefficient between the estimated and observed values significantly increased to 0.89, the RMSE decreased to 0.65 mm·d^-1, and the Nash-Sutcliffe efficiency coefficient reached 0.79. These results indicate that the proposed method effectively improves the estimation accuracy of the three-temperature remote sensing evapotranspiration model and offers insights for enhancing the accuracy of other remote sensing evapotranspiration models.

Key words: harmonic analysis of time series, adjoint calibrated function, k-means++ algorithm, crop growth model, evapotranspiration

FENG Kepeng, XU Dehao, ZHUANG Haoran. An estimation method of remote sensing evapotranspiration in farmland based on the three-temperature model with adjoint calibrated of WOFOST[J].Arid Zone Research, 2025, 42(1): 166-178.

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参数	定义	取值	参数	定义	取值
TSUM1	出苗至抽雄有效积温	1026	AMAXTB1.75		49
TSUM2	抽雄至成熟有效积温	889	AMAXTB2.0		42
DTSMTB0	积温日增长函数	0	KDIFTB0.0	可见光漫反射消光系数函数	0.6
DTSMTB6		0	KDIFTB2.0		0.6
DTSMTB30		22	EFFTB0.0	叶片光合作用效率函数	0.45
DTSMTB35		24	EFFTB40.0		0.45
TDWI	初始地上总生物量	18	CVL	叶同化物转换效率	0.680
LAIEM	出苗时叶面积指数	0.00836	CVO	贮存器官同化物转换效率	0.665
RGRLAI	叶面积指数最大增长速率	0.00294	CVR	根同化物转换效率	0.690
SLATB0.0	比叶面积函数	0.0025	CVS	茎同化物转换效率	0.682
SLATB0.78		0.0014	RML	叶相对维持呼吸速率	0.03
SLATB2.0		0.0014	RMO	贮存器官相对维持呼吸速率	0.01
SPAN	叶片衰老系数	42	RMR	根相对维持呼吸速率	0.015
TBASE	叶片生长下限温度	8	RMS	茎相对维持呼吸速率	0.015
AMAXTB0.0	最大CO₂同化速率	70	SMW	萎蔫点含水量	0.10
AMAXTB1.25		63	SMFCF	田间持水量下的土壤含水量	0.27
AMAXTB1.50		49	SM0	饱和含水量	0.40

An estimation method of remote sensing evapotranspiration in farmland based on the three-temperature model with adjoint calibrated of WOFOST

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